Computer Vision Engineer

Placements24

Noord-Kaap

Hybrid

ZAR 600,000 - 900,000

Full time

14 days+
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Benefits offered by this job

Performance bonuses
Fully remote
Flexible hours
Professional development
Global team collaboration

Job summary

Placements24 is seeking a skilled Computer Vision Engineer to join its R&D team in a fully remote role. You will design, develop, and implement advanced CV algorithms for a range of applications, including image recognition, object tracking, and 3D reconstruction, collaborating with a global team.

The role requires a Master''s or Ph.D. in a CV-focused field, 4+ years of hands-on experience, strong C++ and Python skills, and practical use of OpenCV and dlib, with TensorFlow/PyTorch/Keras for deep

Qualifications

  • Master's or PhD in CS/EE with focus on computer vision.
  • 4+ years of experience developing computer vision algorithms and applications.
  • Strong proficiency in C++ and Python with OpenCV and dlib.
  • Expertise in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
  • Experience with image processing techniques and mathematical optimization.
  • Excellent problem-solving skills and ability to work remotely with a global team.

Responsibilities

  • Develop and optimize computer vision algorithms for image analysis and understanding.
  • Implement ML models for object detection, classification, and segmentation.
  • Design and build systems for real-time video processing and analysis.
  • Collaborate with software engineers to integrate CV solutions into product pipelines.
  • Conduct research and stay updated on the latest advancements in CV and deep learning.
  • Evaluate and benchmark the performance of CV models and systems.

Skills

Computer Vision
C++
Python
OpenCV
Deep Learning
TensorFlow
PyTorch
3D Reconstruction
dlib

Education

Master's or PhD in CS/EE with CV focus

Tools

OpenCV
dlib

Job description

About the Role

Our client is seeking a skilled Computer Vision Engineer to join their innovative R&D team. This is a fully remote position where you will design, develop, and implement advanced computer vision algorithms and systems for a variety of applications. You will work on challenging problems involving image recognition, object detection, tracking, and 3D reconstruction, contributing to the creation of intelligent visual systems. This role offers an exciting opportunity to work with state-of-the-art technologies and make a significant impact in a flexible, remote-first environment, collaborating with a global team.

Key Responsibilities
  • Develop and optimize computer vision algorithms for image analysis and understanding.
  • Implement machine learning models for tasks such as object detection, classification, and segmentation.
  • Design and build systems for real-time video processing and analysis.
  • Collaborate with software engineers to integrate computer vision solutions into product pipelines.
  • Conduct research and stay updated on the latest advancements in computer vision and deep learning.
  • Evaluate and benchmark the performance of computer vision models and systems.
Requirements
  • Master's or Ph.D. in Computer Science, Electrical Engineering, or a related field with a focus on computer vision.
  • Proven experience (4+ years) in developing computer vision algorithms and applications.
  • Strong proficiency in C++ and Python, and experience with relevant libraries (OpenCV, dlib).
  • Expertise in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
  • Experience with image processing techniques and mathematical optimization.
  • Excellent problem-solving skills and ability to work effectively in a remote collaborative setting.
Benefits
  • Competitive salary and performance bonuses.
  • Comprehensive health, dental, and vision insurance.
  • Fully remote work arrangement with flexible hours.
  • Significant opportunities for professional development and learning.
  • Chance to work on groundbreaking AI projects with real-world impact.
  • Supportive team culture focused on innovation and collaboration.
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